A Socio-Technical Approach to Designing a Visual Analytics Decision Support Tool for Wind Farm Placement Planning in Alberta
Abstract
Wind energy is recognized as an important component of the world’s energy mix. Despite its widely acknowledged advantage as a renewable energy resource, the development of wind farms in the last 20 years has posed a critical challenge for land use planning in Alberta. In view of this, there are compelling arguments that effective, place-specific decision support tools would enable stakeholders identify appropriate placement locations for wind farms in Alberta. The research presented in thesis empirically examined ways in which a decision support tool can be developed to achieve the goal stated above. A socio-technical approach was used to identify the decision support requirements of wind energy stakeholders in Alberta and to develop a conceptual framework in response to the requirements. Further research was conducted to determine the underlying attributes of effective visual analytics decision support tools, and how those attributes can be applied to the design of the proposed tool. Based on the established requirements, attributes, and conceptual framework, a proof-of-concept, web-based Alberta Wind decision support tool (AB–WINDEC) tool was implemented using iterative prototyping techniques. The prototype was first assessed through an expert appraisal. It was subsequently evaluated in focus groups with wind energy stakeholders in Alberta. Focus group participants reviewed the conceptual system design in the following areas: usability, usefulness, analytical support, and capability to support tasks and data management. These findings suggest that AB–WINDEC can be useful for educational purposes, public engagement, high-level analysis, risk assessment, and collaboration. The main contributions of this thesis and the research described in it are four-fold: It extends current knowledge by bringing together, for the first time, the decision support requirements of stakeholders involved in planning the placement of wind farms in Alberta. Thus, it was possible to develop a conceptual framework that integrated the dual aspects of AB–WINDEC as a social and technical decision support tool. Progress was made in multi-disciplinary areas of visual analytics, product design, product experience, prototyping, and design research. Finally, the thesis shows that knowledge gained from empirical research can inform the development of an effective visual analytics decision support tool.
Description
Keywords
Energy, Engineering--Environmental, Psychology--Social
Citation
Adagha, O. (2016). A Socio-Technical Approach to Designing a Visual Analytics Decision Support Tool for Wind Farm Placement Planning in Alberta (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25011